IDEAS home Printed from https://ideas.repec.org/a/eas/econst/v10y2018i10p77-84.html
   My bibliography  Save this article

A Bayes Network Analysis For Banking'S Consumer Loan Allocation

Author

Listed:
  • Volkan SEVÄ°NÇ

    (Muğla Sıtkı Koçman Üniversitesi Fen Fakültesi, Kötekli Kampüsü, Muğla, Yrd. Doç. Dr.)

Abstract

One of the solutions that consumers apply to afford some of their needs is consumer credit. Consumer credits mainly form three groups: Mortgage credits, personal finance credits and vehicle credits. When banks are allocating those credits to their customers they make an evaluation of the customers according to some criteria. At the end of this evaluation they accept or reject the credit demands. This manuscript provides a simultaneous analysis of the variables belonging to the consumer credit customers by means of a Bayesian network. The analysis includes the relationship of the variables with each other and the decision of the bank. According to the analysis it has been detected that banks tend to give the personal finance credit more easily to the all age and occupation groups. The mortgage credit, however, is the most difficult to get. As far as the vehicle credit applications are concerned, age appears to be an important factor to get the credit.

Suggested Citation

  • Volkan SEVÄ°NÇ, 2018. "A Bayes Network Analysis For Banking'S Consumer Loan Allocation," Eurasian Eononometrics, Statistics and Emprical Economics Journal, Eurasian Academy Of Sciences, vol. 10(10), pages 77-84, February.
    • Handle: RePEc:eas:econst:v:10:y:2018:i:10:p:77-84
    DOI: 10.17740/eas.stat.2018�V10�06
    as

    Download full text from publisher

    File URL: https://eurasianacademy.org/index.php/econstat/article/view/967
    Download Restriction: no
    File URL: https://libkey.io/10.17740/eas.stat.2018�V10�06?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eas:econst:v:10:y:2018:i:10:p:77-84. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kutluk Kagan Sumer (email available below). General contact details of provider: https://www.eurasianacademy.org/index.php/econstat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.